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| import express from "express" | |
| import { HfInference } from '@huggingface/inference' | |
| import { daisy } from "./daisy.mts" | |
| import { alpine } from "./alpine.mts" | |
| const hf = new HfInference(process.env.HF_API_TOKEN) | |
| // TODO put here the Inference Endpoint url for WizardCoder | |
| const model = hf.endpoint('https://xyz.eu-west-1.aws.endpoints.huggingface.cloud/gpt2'); | |
| // define the CSS and JS dependencies | |
| const css = [ | |
| "/css/[email protected]", | |
| ].map(item => `<link href="${item}" rel="stylesheet" type="text/css"/>`) | |
| .join("") | |
| const script = [ | |
| "/js/[email protected]", | |
| "/js/[email protected]" | |
| ].map(item => `<script src="${item}"></script>`) | |
| .join("") | |
| const app = express() | |
| const port = 7860 | |
| const minPromptSize = 16 // if you change this, you will need to also change in public/index.html | |
| const timeoutInSec = 3 * 60 | |
| console.log("timeout set to 3 minutes") | |
| app.use(express.static("public")) | |
| const pending: { | |
| total: number; | |
| queue: string[]; | |
| } = { | |
| total: 0, | |
| queue: [], | |
| } | |
| const endRequest = (id: string, reason: string) => { | |
| if (!id || !pending.queue.includes(id)) { | |
| return | |
| } | |
| pending.queue = pending.queue.filter(i => i !== id) | |
| console.log(`request ${id} ended (${reason})`) | |
| } | |
| app.get("/debug", (req, res) => { | |
| res.write(JSON.stringify({ | |
| nbTotal: pending.total, | |
| nbPending: pending.queue.length, | |
| queue: pending.queue, | |
| })) | |
| res.end() | |
| }) | |
| app.get("/app", async (req, res) => { | |
| if (`${req.query.prompt}`.length < minPromptSize) { | |
| res.write(`prompt too short, please enter at least ${minPromptSize} characters`) | |
| res.end() | |
| return | |
| } | |
| const id = `${pending.total++}` | |
| console.log(`new request ${id}`) | |
| pending.queue.push(id) | |
| const prefix = `<html><head>${css}${script}` | |
| res.write(prefix) | |
| req.on("close", function() { | |
| // console.log("browser asked to close the stream for some reason.. let's ignore!") | |
| endRequest(id, "browser asked to end the connection") | |
| }) | |
| // for testing we kill after some delay | |
| setTimeout(() => { | |
| endRequest(id, `timed out after ${timeoutInSec}s`) | |
| }, timeoutInSec * 1000) | |
| const finalPrompt = `# Task | |
| Generate the following: ${req.query.prompt} | |
| # Documentation | |
| ${daisy} | |
| # Guidelines | |
| - Never repeat the instruction, instead directly write the final code within a script tag | |
| - Use a color scheme consistent with the brief and theme | |
| - You need to use Tailwind CSS and DaisyUI for the UI, pure vanilla JS and AlpineJS for the JS. | |
| - All the JS code will be written directly inside the page, using <script type="text/javascript">...</script> | |
| - You MUST use English, not Latin! (I repeat: do NOT write lorem ipsum!) | |
| - No need to write code comments, and try to make the code compact (short function names etc) | |
| - Use a central layout by wrapping everything in a \`<div class="flex flex-col justify-center">\` | |
| # HTML output | |
| ${prefix}` | |
| try { | |
| let result = '' | |
| for await (const output of hf.textGenerationStream({ | |
| inputs: finalPrompt, | |
| parameters: { max_new_tokens: 1024 } | |
| })) { | |
| if (!pending.queue.includes(id)) { | |
| break | |
| } | |
| result += output.token.text | |
| process.stdout.write(output.token.text) | |
| res.write(output.token.text) | |
| if (result.includes('</html>')) { | |
| break | |
| } | |
| } | |
| endRequest(id, `normal end of the LLM stream for request ${id}`) | |
| } catch (e) { | |
| endRequest(id, `premature end of the LLM stream for request ${id} (${e})`) | |
| } | |
| try { | |
| res.end() | |
| } catch (err) { | |
| console.log(`couldn't end the HTTP stream for request ${id} (${err})`) | |
| } | |
| }) | |
| app.listen(port, () => { console.log(`Open http://localhost:${port}/?prompt=a%20pong%20game%20clone%20in%20HTML,%20made%20using%20the%20canvas`) }) | |